I assumed the hard work was just wiring LiveKit/Pipecat + STT/TTS + an LLM. It wasn’t.
Even with solid OSS (Pipecat/LiveKit), we still had to do a lot of plumbing- variable extraction, tracing, testing etc and any workflow changes required constant redeploys.
We eventually realized we’d spent more time building infrastructure than building the actual agents. Everything felt custom. We hit every possible pain with Pipecat and VAPI style systems.
So we built Dograh - a fully open-source voice agent framework that includes all the boring, painful pieces by default.
What’s different:
- Pipecat-based engine, but forked - custom event model, and concurrency fixes
- One-click start template generated by an LLM Agent for a quick get start template for any use case
- Drag-and-drop visual agent builder for quick iteration (the thing we wished existed earlier)
- Variable extraction layer (name/order/date/etc.) baked into the LLM loop
- Built in Telephony integration (Twilio/ Vonage/ Vobiz/ Cloudonix)
- Multilingual support end-to-end
- Select any LLM TTS STT (add their credits, if any)
- AI-to-AI call testing: automatically stress-test an agent before shipping (still a work in progress- so patchy as of now)
- Fully Open Source
It's built and maintained by YC alumni / exit founders who got tired of rebuilding the same plumbing.
Why we open-sourced it: We kept feeling that the space was drifting toward closed SaaS abstractions (VAPI, Retell). Those are good for demos, but once you need data controls, privacy or self/offline deployment, you end up stuck. We wanted a stack where you can see every part, fork it, self-host it, and patch it as needed.
Try it:
- Repo: https://github.com/dograh-hq/dograh
This spins up a basic multilingual agent with everything pre-wired.
Who this is for:
- If you are looking for self hosting a Vapi like platform for Data Privacy etc.
- Anyone trying to build production-grade voice agents without reinventing audio plumbing.
- If you’ve tried to glue STT→LLM→TTS manually, you probably know the exact pain this is built for
Happy to answer technical questions, show the architecture, or hear how we can improve the product.
a6kme•2mo ago
But when we switched to OSS stacks (Pipecat, LiveKit), we realise that even with great OSS, the plumbing was still painful and necessary- no standard way to extract variables from conversations (name/date/order ID), no straightforward tracing of LLM calls, no way to run AI-to-AI test loops, and no fast workflow iteration - and every change meant another redeploy.
The infrastructure glue kept ballooning, and each time it felt like rebuilding the same system from scratch.
Dograh came out of that combination of cost pain and integration pain. Happy to dig deeper into anything.